Computational Training Workshop for Infectious Disease Epidemiology

 

 

November 2021 - Le Gourmet Ankorondrano Antananarivo, Madagascar

 

 

Ministry of Health, Department of Public Health of the Faculty of Medicine of the University of Madagascar
Mahaliana Laboratory, Antananarivo, Madagascar
Princeton University, USA

Johns Hopkins University, USA

 

 


Through an integrated curriculum that combines data analyses (statistical, management, visualization) with applied public health questions, participants will gain skills to answer applied public health policy and research questions. This course does not require any previous experience in using R or similar statistical software, but does require the participant is actively working on epidemiological research and/or public health by analyzing and visualizing data. The course will be a combination of hands-on activities and lectures. Sessions will include both guided lessons and open office hours to provide time and assistance for individual research or public health projects. Students and practitioners who are already actively involved in research related to these topics are encouraged to participate. See below for eligibility. The course will be taught in French and English but instructors will be available to further explain in Malagasy and/or French when needed.

 

 

Please fill out the form

 

 

 
 
 
 
 
 
Schedule of activities
Course material

Day 1 (introduction to R) 
Introduction and introduction to the course 
Introduction to R and R studio
Working with Dplyr to produce summary statistics (include group by, filter etc....
 
 
Day 2 (ggplot and figures)
intro course on scientific figures, when to use which kind of figure etc...
brief course spatial intro to build maps
tutorial build a few figures using provided dataset (a choropleth map, a time series, and one or 2 other random figures)

 
Day 3 (communicate results through reports and dashboard)
intro to Rmarkdown (using the figures built on day 2)
how to use R markdown to build a report that is easy to reproduce and update 
and use Rmarkdown to build a dashboard.